Meta-Ribosomalomics: RNA Sequencing Is an Unbiased Method for Parasite Detection of Different Sample Types

Non-Targeted RNA Sequencing: Towards the Development of Universal Clinical Diagnosis Methods for Human and Veterinary Infectious Diseases

Metagenomics offers the potential to replace and simplify classical methods used in the clinical diagnosis of human and veterinary infectious diseases. Metagenomics boasts a high pathogen discovery rate and high specificity, advantages absent in most classical approaches. However, its widespread adoption in clinical settings is still pending, with a slow transition from research to routine use. While longer turnaround times and higher costs were once concerns, these issues are currently being addressed by automation, better chemistries, improved sequencing platforms, better databases, and automated bioinformatics analysis. However, many technical options and steps, each producing highly variable outcomes, have reduced the technology's operational value, discouraging its implementation in diagnostic labs. We present a case for utilizing non-targeted RNA sequencing (NT-RNA-seq) as an ideal metagenomics method for the detection of infectious disease-causing agents in humans and animals. Additionally, to create operational value, we propose to identify best practices for the "core" of steps that are invariably shared among many human and veterinary protocols. Reference materials, sequencing procedures, and bioinformatics standards should accelerate the validation processes necessary for the widespread adoption of this technology. Best practices could be determined through "implementation research" by a consortium of interested institutions working on common samples.

The Core Human Microbiome: Does It Exist and How Can We Find It? A Critical Review of the Concept

The core microbiome, which refers to a set of consistent microbial features across populations, is of major interest in microbiome research and has been addressed by numerous studies. Understanding the core microbiome can help identify elements that lead to dysbiosis, and lead to treatments for microbiome-related health states. However, defining the core microbiome is a complex task at several levels. In this review, we consider the current state of core human microbiome research. We consider the knowledge that has been gained, the factors limiting our ability to achieve a reliable description of the core human microbiome, and the fields most likely to improve that ability. DNA sequencing technologies and the methods for analyzing metagenomics and amplicon data will most likely facilitate higher accuracy and resolution in describing the microbiome. However, more effort should be invested in characterizing the microbiome’s interactions with its human host, including the immune system and nutrition. Other components of this holobiontic system should also be emphasized, such as fungi, protists, lower eukaryotes, viruses, and phages. Most importantly, a collaborative effort of experts in microbiology, nutrition, immunology, medicine, systems biology, bioinformatics, and machine learning is probably required to identify the traits of the core human microbiome.

Molecular Detection of Malpighamoeba mellificae in Honey Bees

Malpighamoeba mellificae is a protozoan that infects the Malpighian tubules of honey bees. The amoebae, ingested as cysts, develop into trophozoites that feed upon tubule epithelia. The resulting damage of the Malpighian tubules can induce an imbalance of waste excretion and hemolymph exchange. This causes the so-called amoebiasis disease in adult bees, which may co-occur with Nosema infections. Most reports of this amoeba are from the 1960s and earlier, and knowledge of the disease and its spreading is very poor. The lack of any genetic marker for the species hampers its sensitive identification using molecular tools and gaining knowledge on its epidemiology. Here, we present a diagnostic RT-qPCR assay, consisting of two primers and one probe that were developed based on 18S rRNA sequences of the amoeba, generated with metagenomic sequencing of Malpighian tubules with and without M. mellificae cysts. The assay was initially tested and adjusted with samples microscopically tested for the presence of M. mellificae cysts. Later, it was validated and material with unknown infection status was tested. The sensitive diagnostic Malpighamoeba disease 18S assay is now ready to be applied for honey bee health monitoring purposes and to investigate the prevalence of M. mellificae in more detail.